AI Bias Worksheet for Kids

AI for students lesson 7: Bias: when data is unfair · Set 691 · 40 questions

AI tip (Fair data, fairer AI): Bias usually comes from the training data: if a group is missing or shown in only one way, the model copies that. One-sided data: one age group, only ripe mangoes, only adult voices, only neat handwriting. Balanced data: many ages, colours, voices, regions and styles. Reduce bias: add varied examples, check who is missing, test on many groups, fix wrong labels and listen to complaints.

1. 1.🛠️ Does this reduce bias or add to it: ignore complaints? (a) adds to bias (b) reduces bias
2. 2.Which of these helps reduce bias? (a) copy old unfair choices (b) ask different people (c) add more of the same (d) ignore complaints
3. 3.🗣️ A voice app understands adults but not children. What is the likely reason? (a) children speak too fast (b) the phone was new (c) it was a rainy day (d) few child voices in data
4. 4.🔍 Which is the odd one out? (a) check who is missing (b) add varied examples (c) ask different people (d) ignore complaints
5. 5.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
6. 6.🔍 Which is the odd one out? (a) check who is missing (b) ignore complaints (c) test on one group only (d) copy old unfair choices
7. 7.🛠️ Does this reduce bias or add to it: check who is missing? (a) adds to bias (b) reduces bias
8. 8.Which of these helps reduce bias? (a) test on one group only (b) copy old unfair choices (c) test on many groups (d) ignore complaints
9. 9.🔍 Which is the odd one out? (a) add varied examples (b) test on many groups (c) fix wrong labels (d) test on one group only
10. 10.True or false: “balance the data” helps reduce bias. (a) False (b) True
11. 11.Which of these adds to bias? (a) ask different people (b) check who is missing (c) copy old unfair choices (d) add varied examples
12. 12.🛠️ Does this reduce bias or add to it: add more of the same? (a) reduces bias (b) adds to bias
13. 13.🛠️ Does this reduce bias or add to it: use one group only? (a) reduces bias (b) adds to bias
14. 14.True or false: “skip testing” helps reduce bias. (a) False (b) True
15. 15.True or false: “test on one group only” helps reduce bias. (a) False (b) True
16. 16.⚖️ Where does bias in an AI system usually come from? (a) the weather (b) its colour (c) its training data (d) its screen size
17. 17.⚖️ One-sided or balanced data: stories with doctors of every gender? (a) one-sided data (b) balanced data
18. 18.⚖️ One-sided or balanced data: a fruit sorter shown only ripe mangoes? (a) one-sided data (b) balanced data
19. 19.⚖️ One-sided or balanced data: a voice app trained only on adult voices? (a) balanced data (b) one-sided data
20. 20.True or false: mangoes both raw and ripe is one-sided data (likely to make a biased model). (a) True (b) False
21. 21.True or false: “ignore complaints” helps reduce bias. (a) True (b) False
22. 22.True or false: photos of people from only one age group is one-sided data (likely to make a biased model). (a) False (b) True
23. 23.🔍 Which is the odd one out? (a) check who is missing (b) use one group only (c) test on many groups (d) ask different people
24. 24.🔍 Which is the odd one out? (a) add varied examples (b) fix wrong labels (c) check who is missing (d) copy old unfair choices
25. 25.Which of these adds to bias? (a) add varied examples (b) check who is missing (c) ignore complaints (d) ask different people
26. 26.🖼️ If an image generator always draws a scientist as a man, that shows… (a) a broken screen (b) bias from data (c) a fair model (d) a strong battery
27. 27.True or false: a handwriting app shown only neat writing is one-sided data (likely to make a biased model). (a) True (b) False
28. 28.True or false: “test on many groups” adds to bias. (a) False (b) True
29. 29.🛠️ Does this reduce bias or add to it: skip testing? (a) adds to bias (b) reduces bias
30. 30.🛠️ Does this reduce bias or add to it: copy old unfair choices? (a) adds to bias (b) reduces bias
31. 31.Which of these adds to bias? (a) ask different people (b) add varied examples (c) check who is missing (d) skip testing
32. 32.True or false: “copy old unfair choices” helps reduce bias. (a) True (b) False
33. 33.⚖️ One-sided or balanced data: voices of children and adults from many regions? (a) one-sided data (b) balanced data
34. 34.Which of these helps reduce bias? (a) test on one group only (b) skip testing (c) balance the data (d) add more of the same
35. 35.Which of these helps reduce bias? (a) copy old unfair choices (b) add varied examples (c) skip testing (d) use one group only
36. 36.True or false: voices of children and adults from many regions is balanced data (fairer for everyone). (a) True (b) False
37. 37.True or false: “balance the data” adds to bias. (a) False (b) True
38. 38.True or false: a leaf app trained only on summer leaves is one-sided data (likely to make a biased model). (a) False (b) True
39. 39.🛠️ Does this reduce bias or add to it: add varied examples? (a) reduces bias (b) adds to bias
40. 40.⚖️ One-sided or balanced data: mangoes both raw and ripe? (a) one-sided data (b) balanced data

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